Advanced driver assistance solutions are gaining market day by day. Forward collision warning is one of the application which warns the driver when the host vehicle is about to collide with the preceding target vehicle. The vision application detects the preceding vehicle in day and night time and generates warning based on a calculated time to collision. Forward collision warning systems and other vision based automotive applications use different algorithms to detect vehicles in day and night time conditions.
However, the existing vehicle detection systems are not very efficient, are not convenient and are costly. There is a need for a method and system for vision based night time vehicle detection which is efficient and economical. There is a need for a system that provides a robust detection of vehicles in low light conditions in various real time scenarios and also eliminates false objects.
The conventional visual processing system lacks under a wide range of visibility conditions including country conditions (dark) and city conditions (bright). Additionally, the class of vehicles detection is particularly challenging for a number of reasons including:                Wide variety of vehicles with different position and shape of vehicle lights.        Vehicles with dissimilar lights. Ex., Broken light, Side light ON.        Vehicles with no lights ON.        Vehicle detection in city condition with so many miscellaneous surrounding lights.        Two wheeler detection & distance estimation.        
Therefore, there is a need for a vehicle detection system for detecting one or more vehicles on roads at night time. There is a need for a robust system that can identify and remove false objects that closely resemble vehicle light shapes such as street lights, traffic cones, and miscellaneous light sources; thus, providing high level of accuracy.